Relationship between intrinsic network connectivity and psychiatric symptom severity in functional seizures. Issue 2 (27th October 2022) - Goodman, Adam M; Kakulamarri, Pranav; Nenert, Rodolphe; Allendorfer, Jane B; Philip, Noah S; Correia, Stephen; LaFrance, W Curt; Szaflarski, Jerzy P
Abstract : Background: Traumatic brain injury (TBI) may precipitate the onset of functional seizures (FSs). Many patients with FS report at least one prior TBI, and these patients typically present with more severe psychiatric comorbidities. TBI and psychopathology are linked to changes in neural network connectivity, but their combined effects on these networks and relationship to the effects of FS remain unclear. We hypothesised that resting-state functional connectivity (rsFC) would differ between patients with FS and TBI (FS+TBI) compared with TBI without FS (TBI only), with variability only partially explained by the presence of psychopathology. Methods: Patients with FS+TBI (n=52) and TBI only (n=54) were matched for age and sex. All participants completed psychiatric assessments prior to resting-state functional MRI at 3 T. Independent component analysis identified five canonical rsFC networks related to emotion and motor functions. Results: Five linear mixed-effects analyses identified clusters of connectivity coefficients that differed between groups within the posterior cingulate of the default mode network, insula and supramarginal gyrus of the executive control network and bilateral anterior cingulate of the salience network (all α=0.05, corrected). Cluster signal extractions revealed decreased contributions to each network for FS+TBI compared to TBI only. Planned secondary analyses demonstrated correlations between signal and severity of mood, anxiety, somatisation and global functioning symptoms. Conclusions: These findings indicate the presence of aberrant connectivity in FS and extend the biopsychosocial network model by demonstrating that common aetiology is linked to both FS and comorbidities, but the overlap in affected networks varies by comorbid symptoms.